How should the output layer of an LSTM be when the output are word embeddings?
Actually, LSTM is not used to get word2vec. Indeed, word2vec is extracted from corpus of words using MLP (Multi Layer Perceptron). There is a great tutorial on how to extract word2wec:
http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/

After representing word as vectors, you feed your text to LSTM in a deep architecture which the last layer must be softmax to categorize your text.